|
|
Absolute deviation, 绝对离差% }, y3 }, z2 p. ~; ]5 N% _
Absolute number, 绝对数" x6 R1 s2 A* J( ^ k1 V4 X* V9 k
Absolute residuals, 绝对残差7 A# S7 H- S& `- D1 `6 i% @' [
Acceleration array, 加速度立体阵
# W$ D3 G" K* d! O* qAcceleration in an arbitrary direction, 任意方向上的加速度2 m& e. y6 a7 |
Acceleration normal, 法向加速度
! Q! \$ E- F- SAcceleration space dimension, 加速度空间的维数$ C; C0 Z0 L! A" c: e
Acceleration tangential, 切向加速度/ w$ k$ D& H8 O" r- q
Acceleration vector, 加速度向量
3 u2 P- G9 D! v8 T# C+ F7 I! \Acceptable hypothesis, 可接受假设9 b2 k' I2 y% u: Z) a% m
Accumulation, 累积7 h2 L( @9 J+ u5 j) k
Accuracy, 准确度. a0 g- T8 R: ?7 C* _
Actual frequency, 实际频数0 R `7 {& b8 B# u( N, I- X. C
Adaptive estimator, 自适应估计量
3 Z" F2 F) v" n; T9 KAddition, 相加
0 x; s. n. S) J& m# K# s0 SAddition theorem, 加法定理
. D$ L. A" M1 w# ~0 A5 rAdditivity, 可加性7 s0 P6 z! X }
Adjusted rate, 调整率
* z8 m# L3 E+ N- X! s4 hAdjusted value, 校正值
/ A; P# T& }7 Q& D5 BAdmissible error, 容许误差1 \4 @2 C% f! Z5 h
Aggregation, 聚集性
7 F- ^. f( u& {2 g1 f$ fAlternative hypothesis, 备择假设1 L. b' o9 `. B: V& Q
Among groups, 组间( |2 T+ _; M8 X6 y" m* Y
Amounts, 总量
7 I5 ^& y% E9 W, S2 LAnalysis of correlation, 相关分析4 z. _/ M4 L; x7 c0 \; |+ d9 u. f7 R; Z
Analysis of covariance, 协方差分析 _" V+ Q) u4 G
Analysis of regression, 回归分析3 I7 K1 P! Z, b8 Y' ~9 D* X" P
Analysis of time series, 时间序列分析/ m# v; T4 B0 G# L c
Analysis of variance, 方差分析
! a' u% G- s# A9 H+ bAngular transformation, 角转换% N4 w& h; \* l' g' ^8 Y& W. x
ANOVA （analysis of variance）, 方差分析
/ R5 m0 W7 f8 _$ G" ~ANOVA Models, 方差分析模型
, V! E9 e' c0 J, q2 R8 ~5 ~8 ~: GArcing, 弧/弧旋
3 H$ n6 l4 b) ~Arcsine transformation, 反正弦变换! n- A6 ~. U$ X- \; s1 m8 U' |
Area under the curve, 曲线面积: Q$ v7 D( J, `$ L
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 & G8 n% M1 ?/ {
ARIMA, 季节和非季节性单变量模型的极大似然估计 - v6 J( y( ?6 A: A; K
Arithmetic grid paper, 算术格纸
( t; n) @2 G& D8 t+ U1 A% |1 yArithmetic mean, 算术平均数
8 _; a! a( D/ J% s8 V$ gArrhenius relation, 艾恩尼斯关系- {( f6 [2 P S8 n+ B' s2 v
Assessing fit, 拟合的评估
2 S1 C; G6 g" z4 xAssociative laws, 结合律9 ~# I) o0 G1 r# |- X% a
Asymmetric distribution, 非对称分布/ i0 y0 ^5 I" W E6 C% g( S# j$ E
Asymptotic bias, 渐近偏倚
* B* [- J% o; rAsymptotic efficiency, 渐近效率+ S. q+ o* R; d$ C2 j- s
Asymptotic variance, 渐近方差9 d! g; L, u4 G# [
Attributable risk, 归因危险度9 l1 |! Z, d% I/ V) C% o; q
Attribute data, 属性资料
4 R( b' w1 w# l8 W5 yAttribution, 属性
, x2 C5 f, t7 S$ A" d1 KAutocorrelation, 自相关
: N- \6 z8 g- [/ }& I; F! GAutocorrelation of residuals, 残差的自相关
2 a; }5 w/ @+ C% eAverage, 平均数/ g. L4 t+ P5 k* ]' }
Average confidence interval length, 平均置信区间长度
" w. ]8 K1 ?) f. IAverage growth rate, 平均增长率
$ X- u4 B- x M zBar chart, 条形图6 y+ V: L) P' f. z4 s* e* t
Bar graph, 条形图
7 {% d9 P* E5 P8 c7 zBase period, 基期9 r8 N' n* T. R% e/ f
Bayes' theorem , Bayes定理
* ^4 ~" ~" y* }9 b) EBell-shaped curve, 钟形曲线
6 x; S2 c5 E# j' R0 w- k# \Bernoulli distribution, 伯努力分布
6 _' y" `, N& y3 K* m: L- V. V& aBest-trim estimator, 最好切尾估计量
2 N5 q. C* f5 h7 wBias, 偏性
& @: O) o% X& v @# e# pBinary logistic regression, 二元逻辑斯蒂回归6 |* K' K% c" c6 P& P3 F
Binomial distribution, 二项分布
( n6 [9 b! z4 f% j7 _, mBisquare, 双平方+ C+ g4 v, Z7 T: }( c" x( \
Bivariate Correlate, 二变量相关
$ W$ p# T J7 ~' |Bivariate normal distribution, 双变量正态分布
, e) f# J; \9 q S( rBivariate normal population, 双变量正态总体
. w& [/ k4 f \Biweight interval, 双权区间; {* V# q, r! a* d1 [, z
Biweight M-estimator, 双权M估计量
3 u: N m) m; W5 B' S) d9 oBlock, 区组/配伍组3 p1 ]/ i' O; D, r! p: V7 ~! q
BMDP(Biomedical computer programs), BMDP统计软件包
0 x T# @; x$ U7 c3 s# M8 oBoxplots, 箱线图/箱尾图8 d: p8 D$ w) U( c# ?$ N1 J3 c
Breakdown bound, 崩溃界/崩溃点
1 y9 O4 L% ~# b# p% q1 i, zCanonical correlation, 典型相关) U7 q' g; L8 r4 O" W, e, Q* q
Caption, 纵标目7 y# t9 g* S2 B B
Case-control study, 病例对照研究
& ~/ ?: a3 H. Z. M" _! T- X' XCategorical variable, 分类变量
% n2 L# p. H1 t% \9 O% V' tCatenary, 悬链线
. I! W. s: m; w A: ]2 e; TCauchy distribution, 柯西分布; w4 Y; Y, T0 ? N5 p
Cause-and-effect relationship, 因果关系8 z& x1 l& w5 ?5 m! m2 g
Cell, 单元
/ n c( X/ d* c E4 z% E1 PCensoring, 终检7 K, V! s! T8 T, ^# R' W
Center of symmetry, 对称中心
% _; R0 s- Y4 ?# Y0 iCentering and scaling, 中心化和定标
* E: k3 e2 ~* y) f1 I" QCentral tendency, 集中趋势
" m) `0 P) X5 R' o5 n3 }: I3 ~) y' BCentral value, 中心值
- J; P+ U6 v* a, j/ Z5 f8 kCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
( @$ Q+ |) R1 G3 SChance, 机遇
1 e& X f7 j% U6 [( h$ u( GChance error, 随机误差- c, K+ V. t7 W4 y K
Chance variable, 随机变量' z9 g0 K" g$ |2 P$ E+ i( [& q
Characteristic equation, 特征方程8 d. A i3 X) Y
Characteristic root, 特征根
, p$ p* p) \2 t0 I X7 tCharacteristic vector, 特征向量+ ]6 q, d: H! j* Y4 ?. k
Chebshev criterion of fit, 拟合的切比雪夫准则
7 `- \- q! k9 h, O! p* A AChernoff faces, 切尔诺夫脸谱图
R, K0 Z* O. }Chi-square test, 卡方检验/χ2检验' V; l$ y* B5 U. }/ H/ P% Q
Choleskey decomposition, 乔洛斯基分解- P* c4 U0 \# ?
Circle chart, 圆图 i! j2 G- a$ K* C8 R7 ^' g' M! F
Class interval, 组距
- E0 y* K: _) m0 p7 gClass mid-value, 组中值
2 S$ f6 @8 a% \: V4 y0 ?2 iClass upper limit, 组上限4 I3 o5 s+ T. U$ K8 L4 G* J2 A
Classified variable, 分类变量
. D8 w; w8 [" K+ I, k6 W( G9 eCluster analysis, 聚类分析
& ^# v# Z5 h; ` U+ Q& [Cluster sampling, 整群抽样) J; A$ Y. c' E5 u6 V* }
Code, 代码
5 O( X/ V+ i4 I' Z7 n8 oCoded data, 编码数据
! I U6 f0 J0 t3 kCoding, 编码
5 L( E$ @5 ?1 A* f# u; K7 J, cCoefficient of contingency, 列联系数
; t9 g- o3 Q6 N o. `Coefficient of determination, 决定系数
: J/ V) r- n* `6 u6 X- L" XCoefficient of multiple correlation, 多重相关系数7 q7 [/ d+ V! U
Coefficient of partial correlation, 偏相关系数
8 e; v) `3 h+ K5 \$ ZCoefficient of production-moment correlation, 积差相关系数
' G* Z8 q5 O2 k$ cCoefficient of rank correlation, 等级相关系数1 M* p$ {/ g- @
Coefficient of regression, 回归系数 `; m6 z! m Q% o2 r
Coefficient of skewness, 偏度系数
" f( N7 d2 G# j+ V% o: Q8 Z1 ZCoefficient of variation, 变异系数3 {( s9 ]) V1 T
Cohort study, 队列研究
, v$ h8 {+ R) AColumn, 列
/ h8 d& B1 X$ g5 e# hColumn effect, 列效应
w; f- B1 c2 h+ [! s' B8 a% ]Column factor, 列因素7 r+ v" S& z/ W" p/ _
Combination pool, 合并, {6 q! o# }9 ]
Combinative table, 组合表
& {; q5 A/ c- F; s! I a _( N: YCommon factor, 共性因子* V' }: M2 t' g! j; @6 R
Common regression coefficient, 公共回归系数
) {% V, Y) I# r. R, PCommon value, 共同值
8 T9 R* L4 q. c' D# w6 rCommon variance, 公共方差
) h1 H# Q# R8 uCommon variation, 公共变异
1 [- u, T- U4 |2 H6 ~Communality variance, 共性方差' ]! N2 \. @1 G% v {- M
Comparability, 可比性
0 }4 I* C2 I5 y3 |6 QComparison of bathes, 批比较
9 _/ g5 y" d5 |3 GComparison value, 比较值
, O7 k4 }+ N2 V: ?- f/ sCompartment model, 分部模型
; [) X% g3 S+ O. ]Compassion, 伸缩8 k7 r, h: M% l- A" Z
Complement of an event, 补事件4 ?3 Q! Z# |) F3 L, o
Complete association, 完全正相关6 T& L8 _2 O& U4 N9 v
Complete dissociation, 完全不相关$ {! E! B' h1 y7 d8 N
Complete statistics, 完备统计量! ^ _" s" {# G
Completely randomized design, 完全随机化设计
5 S f& ?* k( n o( eComposite event, 联合事件
. Z" X, ]. B: K) [Composite events, 复合事件
% Q1 A( B9 \( ]! J- ~# X7 tConcavity, 凹性% K& {; n5 i# M, _* p# o( @
Conditional expectation, 条件期望
/ h. l7 C6 d0 Y5 ^3 h$ \$ ]Conditional likelihood, 条件似然2 Y5 o0 u$ A' y: l* p5 H* J
Conditional probability, 条件概率9 _- V( W1 H9 G- V7 X
Conditionally linear, 依条件线性
0 ]5 Y0 U' M% o6 B' Y# jConfidence interval, 置信区间
# f/ z! ]' G# M. A4 v _& TConfidence limit, 置信限
% c% B# k1 o2 p5 I* ~" w( ` c9 IConfidence lower limit, 置信下限
* `( s. Y% V/ s7 ^Confidence upper limit, 置信上限
3 w" @) r; b% g8 x, S, tConfirmatory Factor Analysis , 验证性因子分析
) [. _! j( }4 ?: i sConfirmatory research, 证实性实验研究1 X6 T4 g) u; \* c7 w; R
Confounding factor, 混杂因素. ~" ~2 \+ r, }7 f$ @
Conjoint, 联合分析
2 l. |' n+ C2 j9 [% t1 XConsistency, 相合性/ q! ^' @4 ~5 c) m5 \
Consistency check, 一致性检验- W2 _3 }2 u2 Q9 f
Consistent asymptotically normal estimate, 相合渐近正态估计0 v, B2 ~1 W! S4 }
Consistent estimate, 相合估计
e( E u# e* Y1 Y+ WConstrained nonlinear regression, 受约束非线性回归
/ G" `" k8 P* hConstraint, 约束9 v7 c# h, W- V1 i3 T/ T' l2 c- E: V
Contaminated distribution, 污染分布
% N' n# o. G0 l/ z4 F$ G0 RContaminated Gausssian, 污染高斯分布
" N! P( \ q. v, w% sContaminated normal distribution, 污染正态分布4 Z6 N7 V$ F: d3 A R
Contamination, 污染: ^& a# b' n. h: W5 {0 u2 o
Contamination model, 污染模型
8 b2 ~$ W& k" i9 PContingency table, 列联表
; a [' c$ \* jContour, 边界线1 d5 y7 I# Z. [- z# ~* @ d0 z& A2 A
Contribution rate, 贡献率% M2 ]/ Y7 \, o& O3 R
Control, 对照
7 Z( c) Q) u; ]/ M3 mControlled experiments, 对照实验
0 l; u6 y2 C: x9 @5 C4 o4 M+ k) u3 XConventional depth, 常规深度
+ S% |5 d& J; _8 Y5 ]Convolution, 卷积
+ V' f- d( L1 q/ P# c6 U5 dCorrected factor, 校正因子0 O' O$ z1 L3 E% {, x' x
Corrected mean, 校正均值% `5 Z" N4 \& i- O2 j
Correction coefficient, 校正系数; \7 j$ M, a: {) @# ?# o8 H( I
Correctness, 正确性, D- q/ G' B7 |& l3 U
Correlation coefficient, 相关系数- r- ?0 w# h- S+ W2 x
Correlation index, 相关指数
$ |3 S1 q* P* O4 ZCorrespondence, 对应
5 F: Z& s5 f8 _% u8 ~Counting, 计数" g( i6 C+ e0 b
Counts, 计数/频数
, J+ I( y9 j7 r! ~: nCovariance, 协方差6 D+ W& k, c9 ~' w+ D4 x7 c$ x
Covariant, 共变 0 ^+ J$ r* p: D- C7 t9 i! A
Cox Regression, Cox回归
& d. p7 K. j" [! ^Criteria for fitting, 拟合准则 ^# U0 ?1 |4 k1 z- I" D, n a+ _
Criteria of least squares, 最小二乘准则
$ v: Q) n$ T' s+ s1 S6 J5 ]Critical ratio, 临界比6 C% N9 X; M, K( l' {
Critical region, 拒绝域
. W7 ^+ q. D" o0 Z; MCritical value, 临界值
5 r$ W3 G1 m1 M$ G: {Cross-over design, 交叉设计
; F p0 ~+ i" O4 F% D1 @+ TCross-section analysis, 横断面分析
1 u5 x2 G" b& b* v2 W& y' WCross-section survey, 横断面调查; g+ v& |0 }5 O- l9 X
Crosstabs , 交叉表 : M7 x5 U# ^0 Z4 {! Z( H2 r/ j
Cross-tabulation table, 复合表) S2 @; g' \( T P, W, v
Cube root, 立方根- J# z1 u6 |) {1 k" A+ y
Cumulative distribution function, 分布函数+ U) T4 v! U _2 B
Cumulative probability, 累计概率3 b3 j& m6 X- L
Curvature, 曲率/弯曲 e7 h e$ R: Z5 u# e
Curvature, 曲率0 i1 l% w# r% R: B% p0 I, H3 ~
Curve fit , 曲线拟和
' F# r! v( h$ P+ ]Curve fitting, 曲线拟合
; s8 X, [9 D8 \- f& u. Z# k/ {Curvilinear regression, 曲线回归
) a0 Z5 I5 m. [7 B8 eCurvilinear relation, 曲线关系
. G8 t" Z# x7 Z/ a1 m- T" C& U5 `/ BCut-and-try method, 尝试法
3 H' m4 e/ W: t# m* b' iCycle, 周期7 F, k4 t* l Z* v1 ?2 z5 {
Cyclist, 周期性
& X# h9 T& V6 Z2 ?D test, D检验 s: f+ ^3 F8 K5 Z
Data acquisition, 资料收集
% Q) b+ _9 k& W$ {+ H+ g" L: |Data bank, 数据库
( f9 h7 m# x2 }3 }! a* U/ v/ j: }Data capacity, 数据容量
$ b4 {: X6 q! I8 E% t) p5 M6 IData deficiencies, 数据缺乏
% H) O! u! i+ u1 l+ H- CData handling, 数据处理5 v6 [2 R; Q! ] I' G! w2 i* L
Data manipulation, 数据处理
3 `% ~" I/ s$ k" @- [$ wData processing, 数据处理
( f$ r [% Q1 M, z5 w3 }+ P6 ~Data reduction, 数据缩减
& R S- z; {- t! A$ y% n3 |Data set, 数据集
8 b @% e8 s fData sources, 数据来源- X) }7 Z; ?; p0 V
Data transformation, 数据变换
4 `0 l C0 e6 P& f6 h L9 `/ i$ SData validity, 数据有效性
+ _5 y# z$ n4 J* A g2 O0 {Data-in, 数据输入
1 t- g9 b' K8 N6 H6 P, IData-out, 数据输出
+ r) n* G4 q/ ^8 bDead time, 停滞期0 a( n5 I, z' x0 F3 R
Degree of freedom, 自由度# Q x' C5 n+ ^3 t- Z5 k: [$ k+ d
Degree of precision, 精密度. K" n8 d1 ~1 t! n% t$ G
Degree of reliability, 可靠性程度% T6 G. _5 ^9 t; X. {
Degression, 递减$ [" B! i( c. o3 ^& h& v5 W3 t
Density function, 密度函数6 ]. y- s8 K) {3 R5 N# P
Density of data points, 数据点的密度" w7 [. t2 `9 g" x
Dependent variable, 应变量/依变量/因变量
" `4 Y1 A( \* N' K+ d( A) W! p; LDependent variable, 因变量6 A* S& ^9 o1 I# g1 b
Depth, 深度6 ^% P" t- K4 i" L
Derivative matrix, 导数矩阵( t, j5 B8 x& i- I/ q# l( i* H
Derivative-free methods, 无导数方法
6 t$ R: N- L5 t8 J8 Z: c, W! qDesign, 设计5 X- [' }: {, T$ Z! V! Q
Determinacy, 确定性
$ |5 W1 w! Z0 l/ _8 k# g) HDeterminant, 行列式
) H. A! Z4 ~" n! o" s5 B# }Determinant, 决定因素6 m$ ~. A- A- t- Y0 O. Y
Deviation, 离差! n& w& D8 R+ g! S
Deviation from average, 离均差# }0 ]. o9 l: q
Diagnostic plot, 诊断图" M1 G' l- h& S
Dichotomous variable, 二分变量8 P1 z0 O- B+ W+ Q" w
Differential equation, 微分方程
9 a/ q F+ p: ^ |9 e' A& S/ ^Direct standardization, 直接标准化法$ P: U+ c2 O8 _+ F4 X
Discrete variable, 离散型变量
% G: V: X0 r* ~DISCRIMINANT, 判断
3 f% z" c0 X* ~1 s; d0 hDiscriminant analysis, 判别分析0 m3 H! d8 ]* X* T" _
Discriminant coefficient, 判别系数
, M8 ?, y" S% A9 }# PDiscriminant function, 判别值$ o- y& h/ n! I4 m( T T2 _
Dispersion, 散布/分散度
( V+ v8 R! ]. l+ u8 n/ KDisproportional, 不成比例的
/ |: D' p: u" c/ \/ j& LDisproportionate sub-class numbers, 不成比例次级组含量
/ L) }/ y" _! a$ o; D" gDistribution free, 分布无关性/免分布
! H H6 k9 Z$ y7 pDistribution shape, 分布形状2 b5 _# ]7 r8 t: O2 u, x
Distribution-free method, 任意分布法
8 } }) B, g0 U2 [( s4 PDistributive laws, 分配律5 u: i9 P n$ e# s; D
Disturbance, 随机扰动项7 s; [5 G2 P! O6 {6 Y5 j8 \
Dose response curve, 剂量反应曲线3 Y+ M( B8 i- D6 c: ?+ ?
Double blind method, 双盲法
( B3 M5 m3 q9 N/ UDouble blind trial, 双盲试验
: z5 T. C6 z! QDouble exponential distribution, 双指数分布1 v6 X R/ d$ L" n
Double logarithmic, 双对数
5 B6 p, g) j: N8 P5 F( c PDownward rank, 降秩
) {8 ?$ V- a9 `2 L, Q4 L1 `Dual-space plot, 对偶空间图9 L" N2 M. E0 ^4 T# {5 ?
DUD, 无导数方法
. r+ x' M+ f2 F& Y& f5 V4 TDuncan's new multiple range method, 新复极差法/Duncan新法
0 _8 F; u/ y8 I# P' z% c& a0 d, NEffect, 实验效应$ q0 q; J/ z" h) [3 z1 y
Eigenvalue, 特征值
/ ?! D( }2 i* u/ @) U6 S, CEigenvector, 特征向量
, V# h1 Y" U4 N7 u; I- c5 r9 r" u- V+ KEllipse, 椭圆0 U3 \8 y* Q: s+ E9 F
Empirical distribution, 经验分布) K# s3 X6 u$ o2 D. g
Empirical probability, 经验概率单位3 D1 b! F5 N$ @/ `' ]" ]
Enumeration data, 计数资料
- V( K& _, `! D4 J& v( }Equal sun-class number, 相等次级组含量
9 T. H; h' H1 O9 U2 uEqually likely, 等可能
- f, M r# L9 C9 s% ?4 @Equivariance, 同变性/ ]; x# @) v- s" g5 l/ m
Error, 误差/错误
3 X/ m* F' v$ Q V3 y# z8 lError of estimate, 估计误差; \7 K, X+ F `. j
Error type I, 第一类错误
) h: L8 Y, a7 G( A2 |Error type II, 第二类错误4 w, C8 q+ X! I7 y1 C0 d
Estimand, 被估量% w) l$ E% w# J# X' F5 i7 V: }3 Z
Estimated error mean squares, 估计误差均方4 w$ i7 V# ]' L# c5 |" D
Estimated error sum of squares, 估计误差平方和* M8 L( T/ E! K+ O/ Q7 y
Euclidean distance, 欧式距离 `$ C, M+ u% s# {7 |6 t( L
Event, 事件
- m6 U3 Z6 L5 O6 w3 j2 YEvent, 事件
+ I( E+ l8 R1 ^, IExceptional data point, 异常数据点/ f* r2 A5 k8 i# N; w1 X
Expectation plane, 期望平面
S3 @& G# B7 ^5 _7 \$ ~0 fExpectation surface, 期望曲面
0 b, \1 I8 _' r" g+ O: CExpected values, 期望值' |5 E, p: @# e+ S3 c
Experiment, 实验
; G/ A( R0 @' O$ _$ ?, p* J# LExperimental sampling, 试验抽样 q% P( I2 V& ~
Experimental unit, 试验单位
- T( S5 G+ h0 a, j7 E1 t; y( R# N$ m: DExplanatory variable, 说明变量
3 J, d( ]. b) V6 W$ FExploratory data analysis, 探索性数据分析
5 a1 w+ } x- E0 I8 |5 rExplore Summarize, 探索-摘要 F5 z6 O4 C7 i6 \% c
Exponential curve, 指数曲线. n/ L/ k" h/ g, Q
Exponential growth, 指数式增长
, p: X" f. T7 d$ J- s) MEXSMOOTH, 指数平滑方法 ! _# Z) l' H" ?7 l; ~8 C8 a
Extended fit, 扩充拟合$ R, ] K- J9 C" Q2 ~ P
Extra parameter, 附加参数
3 d* e) B8 @8 ]- i/ @7 @/ W( H- ?& eExtrapolation, 外推法
. X( C0 V" Y) Y# Q+ {Extreme observation, 末端观测值& P+ _" a G; ]
Extremes, 极端值/极值2 a; S4 P' u1 X7 V, z5 Z4 I' X
F distribution, F分布
% e/ t" k0 } ~# W, @' T0 QF test, F检验" B( c# G n6 p6 V% V; D
Factor, 因素/因子 e, j1 e4 ]* P! E/ `3 F) p# ]3 f
Factor analysis, 因子分析
R7 P" C: Q; W' {7 P' L) {; E) ~Factor Analysis, 因子分析
* ] H) W% L6 I( xFactor score, 因子得分 3 b% n% E6 J, v( ~
Factorial, 阶乘& x1 p* C4 O# G
Factorial design, 析因试验设计( q3 n, o" D! C+ ]0 d0 c
False negative, 假阴性5 }5 x) q5 V- Z4 ]$ A$ Y0 m" g! K
False negative error, 假阴性错误
, d- F, C6 g: N1 x) m% \Family of distributions, 分布族. ~5 w# A1 m/ `! j. I
Family of estimators, 估计量族
. O9 n9 b2 \' \ O H( zFanning, 扇面# l/ C0 ]7 o v% @7 W* z% w
Fatality rate, 病死率0 {# r$ L( x T) V- j( y9 ~7 D
Field investigation, 现场调查
. g1 B9 b5 I, {9 h1 J' ]Field survey, 现场调查
|5 I# X* ^2 N) L: A+ M1 fFinite population, 有限总体! ~9 J1 z& C- T. D9 g# ]; X4 t
Finite-sample, 有限样本
m# o' U" [. Q& O! R. rFirst derivative, 一阶导数
* M3 v- k0 G5 m! T0 G1 MFirst principal component, 第一主成分! u7 h( }) G6 e% o2 f4 l4 p
First quartile, 第一四分位数
_& V* |6 B! x; r7 I5 aFisher information, 费雪信息量/ d; J/ i) x! o. P+ r- A* q
Fitted value, 拟合值& I) B3 o( e' g, W8 p
Fitting a curve, 曲线拟合
$ W1 a& x2 ]7 R0 v; @0 J% g) fFixed base, 定基
+ @3 k2 e" a( RFluctuation, 随机起伏: q" G: T9 ~2 \, O/ [0 X
Forecast, 预测
- H9 s) K4 i4 Y# X* r pFour fold table, 四格表5 B* e+ B# P1 g( r0 Y
Fourth, 四分点- H5 B" w" \1 V; M2 h; q
Fraction blow, 左侧比率
9 x+ u% n. d" r. `, V( T0 G6 ^Fractional error, 相对误差6 c! |; a$ |% Q" h* Y: h5 T
Frequency, 频率7 f6 i3 }1 ~) {+ h& B, U0 B
Frequency polygon, 频数多边图, E6 b' ~( U( g1 O
Frontier point, 界限点4 j) H3 y; v/ x" q: d2 ]/ W
Function relationship, 泛函关系
( v) E. ]2 m5 V0 z8 J. BGamma distribution, 伽玛分布5 s2 z1 P& G7 k( Y4 C/ f
Gauss increment, 高斯增量
. K8 h: i9 |0 R( a6 ^) ]Gaussian distribution, 高斯分布/正态分布
/ v' E( O# o. P- K+ c6 L' gGauss-Newton increment, 高斯-牛顿增量3 Y- O- O3 x3 U7 _, k
General census, 全面普查6 S; c& s: ^& H
GENLOG (Generalized liner models), 广义线性模型
2 I6 {0 ?) A6 V4 E- b: }3 d9 I' n. [Geometric mean, 几何平均数. K: ?; }2 e! Z9 h2 P3 z. P
Gini's mean difference, 基尼均差8 Q4 P" J% T+ D$ F+ ~8 [+ I
GLM (General liner models), 一般线性模型 ! A9 `3 v. n) g/ {
Goodness of fit, 拟和优度/配合度
/ @0 `$ L' I0 T" T( mGradient of determinant, 行列式的梯度/ B. a/ y6 q" y/ ?! p; i6 d6 ~8 L
Graeco-Latin square, 希腊拉丁方9 b! i/ I8 N& h4 [6 s
Grand mean, 总均值( N9 ^; Y# h& l; R K( q
Gross errors, 重大错误9 J' }* y0 d& \8 i
Gross-error sensitivity, 大错敏感度2 f+ v1 W% v0 b3 y
Group averages, 分组平均
1 O* X# o% R6 I2 K0 ]Grouped data, 分组资料
; @3 K$ B* h* C0 m: _Guessed mean, 假定平均数' `8 ]$ O) Q# O+ g; l) @9 x- l
Half-life, 半衰期
U) @2 W# i; V* k2 lHampel M-estimators, 汉佩尔M估计量# A+ g" N5 p+ q
Happenstance, 偶然事件' Q4 B) _! } Q, z/ B- }! @; t
Harmonic mean, 调和均数
+ H/ d) R" @! P) g$ R' u; }. z q0 z aHazard function, 风险均数
& }/ O% d0 d* W }! |( FHazard rate, 风险率
( d) I. J, [7 D( W" dHeading, 标目 ( L# n2 C `- d0 P2 J$ G' L
Heavy-tailed distribution, 重尾分布5 `, O" w7 r$ b; \* T7 K
Hessian array, 海森立体阵* o T" R: B( c1 C7 Z
Heterogeneity, 不同质
3 r- P: F/ t- J% U: ^# b0 qHeterogeneity of variance, 方差不齐 ) D( K# h2 E' ?0 a N5 j
Hierarchical classification, 组内分组# O/ t4 {2 o4 V* G3 n
Hierarchical clustering method, 系统聚类法
1 v4 l7 F X4 ?) M' ?" X- [$ P" u- KHigh-leverage point, 高杠杆率点
) U2 W' `# A, ]; HHILOGLINEAR, 多维列联表的层次对数线性模型! D" X: K& \0 @2 u& O$ a" j
Hinge, 折叶点: u) u J5 N8 v- X
Histogram, 直方图
3 ?! A$ _# `0 d) Q) z5 r6 vHistorical cohort study, 历史性队列研究
8 I# t3 |" C8 }6 z6 ]% cHoles, 空洞
/ T7 q& [8 `* Q: X8 z( M8 `HOMALS, 多重响应分析4 Z, `$ N u2 F: k/ A( ]7 l9 a
Homogeneity of variance, 方差齐性
4 M2 t/ P) ^0 bHomogeneity test, 齐性检验, j: N) D! ^. `* q: d
Huber M-estimators, 休伯M估计量; k1 w* q$ o& [5 B. L, e$ g
Hyperbola, 双曲线2 a. r( g/ z1 s- i
Hypothesis testing, 假设检验3 f+ `" f( C4 s! G+ c5 d
Hypothetical universe, 假设总体
9 u+ q- Q: L* H; QImpossible event, 不可能事件
$ J. i3 J' W% _Independence, 独立性
9 K' h9 R( m) y* A" f6 kIndependent variable, 自变量# N: N( h. D6 P- @" K( `+ V3 e) G! Y
Index, 指标/指数% g( p9 B0 [# E2 z- A# d1 Z3 e
Indirect standardization, 间接标准化法
( M' n( A% l4 O, fIndividual, 个体
6 M+ D' U( h2 k0 R' T# k" AInference band, 推断带4 f8 C, A: i3 @. A
Infinite population, 无限总体; a* V& M, T9 y5 a& [
Infinitely great, 无穷大
* K* p/ i9 W, L. P7 B! Z" z0 WInfinitely small, 无穷小8 c- V. D' L$ e) t d
Influence curve, 影响曲线$ n9 _% l" N- H% G: u" K
Information capacity, 信息容量3 c/ U/ E: L4 t
Initial condition, 初始条件- \# D% m0 Y4 O
Initial estimate, 初始估计值/ ~/ U9 \) K5 `5 e( R8 X
Initial level, 最初水平( i. R# W0 P6 P K+ ^
Interaction, 交互作用2 k' M3 y9 c; j& ?8 T$ F
Interaction terms, 交互作用项, r# O3 \% f( T( f7 i
Intercept, 截距
; a$ F% n9 }) yInterpolation, 内插法
$ |; I2 U2 v6 c) a) E8 dInterquartile range, 四分位距
; @, X7 ?( t+ [ [3 K1 U! f/ u6 sInterval estimation, 区间估计# Q' e3 {5 B d( Y% D
Intervals of equal probability, 等概率区间
# ]4 _/ Y- E/ d% `Intrinsic curvature, 固有曲率
# Z& b/ u" G+ v% F* GInvariance, 不变性
: ^, d+ h1 W3 ]Inverse matrix, 逆矩阵# G! |/ |. O) E0 z) |
Inverse probability, 逆概率
' X% J# l M& E: ~8 Y1 y3 \Inverse sine transformation, 反正弦变换9 ?8 i. c! h* H) H/ x
Iteration, 迭代
- T* ?6 I% K( u2 \Jacobian determinant, 雅可比行列式1 ~' H& A1 w$ b& ?, |, j
Joint distribution function, 分布函数0 R4 m, R8 Z+ l& a
Joint probability, 联合概率, i: ^4 f% J: t. K. Z& |
Joint probability distribution, 联合概率分布/ [: J: g5 q% W. W$ w, ~! A1 p
K means method, 逐步聚类法# ~4 `) k: m: g( i' A* }0 L; k
Kaplan-Meier, 评估事件的时间长度 ' x ]5 C% a# i6 B3 c+ T
Kaplan-Merier chart, Kaplan-Merier图7 e7 e0 _; x+ @( X F: B
Kendall's rank correlation, Kendall等级相关0 E0 m' z4 T+ j( J1 j6 i( c
Kinetic, 动力学7 d+ h; Y/ Z0 G
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验' |' a5 I/ t$ ?' \( E3 T* Z3 i
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验4 g" k5 n a2 f/ V- ] u% r; ]
Kurtosis, 峰度& e: O2 w p/ e1 I
Lack of fit, 失拟3 z* U# e5 f( n ~( ~
Ladder of powers, 幂阶梯
/ f4 A* A3 l7 ^Lag, 滞后- d: w: j* Z q5 ^( d$ {, m$ d# F
Large sample, 大样本3 X4 F1 g! b, M7 P5 b2 ^
Large sample test, 大样本检验
% v: |- ~* q6 ~Latin square, 拉丁方
: ]$ @2 f6 ?0 O9 K+ v0 cLatin square design, 拉丁方设计5 d- }# C3 f# E" P9 n; {
Leakage, 泄漏, z6 x ]# V, ~5 O8 f+ k
Least favorable configuration, 最不利构形
" c" l: S, P/ U9 L r. k9 \Least favorable distribution, 最不利分布" q+ M" C K! V2 g! r. o
Least significant difference, 最小显著差法1 L! U2 I: L4 n# J7 k
Least square method, 最小二乘法
8 k0 ~/ e1 ~( Y* Q4 O0 t% lLeast-absolute-residuals estimates, 最小绝对残差估计
' |8 C0 g, @7 P$ m8 cLeast-absolute-residuals fit, 最小绝对残差拟合: |0 x# n. n! F' x6 w+ t# q
Least-absolute-residuals line, 最小绝对残差线
4 m! S# O. Y- U3 `2 S2 ALegend, 图例, `4 h3 @* C1 Y% @8 y4 E
L-estimator, L估计量
8 @$ s# s# l& e: q% zL-estimator of location, 位置L估计量
1 I; Y( V) N; u: wL-estimator of scale, 尺度L估计量
8 S; i+ H, |4 RLevel, 水平
x( l# i2 B$ l- f/ qLife expectance, 预期期望寿命" d- f; d* S+ G# M
Life table, 寿命表
2 s- i+ H0 O1 m& U4 w4 `6 JLife table method, 生命表法
, P2 e. ^8 \% a1 a( x$ i* sLight-tailed distribution, 轻尾分布
* z8 K: w6 t. Z: H1 mLikelihood function, 似然函数4 l: \4 R2 ^# c" T
Likelihood ratio, 似然比- x7 }3 A* F5 p! {! H
line graph, 线图' v* m' l+ k9 u4 g8 m. v s
Linear correlation, 直线相关
. V$ K; e+ a+ W5 s" ~Linear equation, 线性方程
, S8 Y+ } ]3 wLinear programming, 线性规划0 Q0 G$ B3 X5 z
Linear regression, 直线回归
3 T4 s! ~! J6 E& @Linear Regression, 线性回归
) ]2 ^2 D9 h9 k: E# F$ U1 M/ QLinear trend, 线性趋势
. ^: |$ x) S7 C% f! _Loading, 载荷 ' I7 ^2 x9 k1 |
Location and scale equivariance, 位置尺度同变性
* W, t& P F4 x1 P4 w8 V+ w$ VLocation equivariance, 位置同变性
9 D9 e- P3 _1 }! _0 e5 `- m7 ILocation invariance, 位置不变性8 k8 w1 `6 P; [% o6 g
Location scale family, 位置尺度族, v0 J4 E+ ]& j( E$ i
Log rank test, 时序检验
/ Q# c2 Z! i w- gLogarithmic curve, 对数曲线; q7 m) V* r2 l% T5 F, ~+ U! W
Logarithmic normal distribution, 对数正态分布
' m$ |0 r; c( k0 f0 f" ]: R$ \Logarithmic scale, 对数尺度 v' T2 p$ M; h
Logarithmic transformation, 对数变换# Q: ^( e# x [* l
Logic check, 逻辑检查
- v- P' n5 V! \5 kLogistic distribution, 逻辑斯特分布3 `! T) s/ |& [% i. L, ]4 R
Logit transformation, Logit转换: R. S4 P! q- I9 y$ K7 v; A' ^7 P
LOGLINEAR, 多维列联表通用模型 # T4 a/ z* u! _
Lognormal distribution, 对数正态分布: k+ t% P) Y9 O! F+ ]8 q; m; g9 L; k) f
Lost function, 损失函数5 f: a6 m, j6 N4 S
Low correlation, 低度相关
+ ^! b7 Y" G) \$ FLower limit, 下限
5 B$ a V- y6 O1 E, W6 nLowest-attained variance, 最小可达方差
2 ~/ A" Y: q* J3 a/ FLSD, 最小显著差法的简称! R! C7 Q6 \# c# l
Lurking variable, 潜在变量) N l& E8 ]/ j/ W4 L Y) i- i
Main effect, 主效应
5 r: u' D x1 A- M: `2 A0 h# FMajor heading, 主辞标目
: S9 s5 g5 A- ?' N: }# UMarginal density function, 边缘密度函数4 w* @3 V% E( R9 j6 j
Marginal probability, 边缘概率. Q5 k' D- g3 V8 C
Marginal probability distribution, 边缘概率分布' e3 j& N; L" z2 \. d
Matched data, 配对资料/ E" E( i! {4 v. s
Matched distribution, 匹配过分布4 V9 @' a+ I6 ^% [. [/ U
Matching of distribution, 分布的匹配
. S( m4 e9 ?- r: ]* ` tMatching of transformation, 变换的匹配6 {1 C5 z' I$ T) g. P
Mathematical expectation, 数学期望: V, F. S' N2 ` e2 k& B
Mathematical model, 数学模型2 m) W& G8 ~! t8 s, G+ x
Maximum L-estimator, 极大极小L 估计量
' M2 T. j, C; YMaximum likelihood method, 最大似然法, P7 D! a! m) X. R: r, w
Mean, 均数
2 b L6 e4 p' g0 IMean squares between groups, 组间均方
% j- K+ o% ^; P. f. p5 m& @+ [Mean squares within group, 组内均方 |+ J9 p" _7 i
Means (Compare means), 均值-均值比较. A: ?, j* w( ?: R
Median, 中位数
% Y+ P: U" k5 {; W. ZMedian effective dose, 半数效量- v9 P2 d P. {+ l9 _
Median lethal dose, 半数致死量6 ?+ I* x, i$ K4 L
Median polish, 中位数平滑7 N1 c0 g5 }! I( \
Median test, 中位数检验
0 x; A" M3 x) z. ?Minimal sufficient statistic, 最小充分统计量
7 Z8 w, X! ^+ G+ F5 TMinimum distance estimation, 最小距离估计8 y8 z" @: s; c# ?! T" Y
Minimum effective dose, 最小有效量
& h, D1 i0 P) b7 E) IMinimum lethal dose, 最小致死量6 p4 g5 e* a7 `6 t
Minimum variance estimator, 最小方差估计量
1 l: @6 l) j2 s1 l% KMINITAB, 统计软件包
1 ~3 P& @% [- O N. @6 K4 X0 eMinor heading, 宾词标目
( Y6 ~" o! ~7 F" v% [9 D; `Missing data, 缺失值/ s) M4 k- E# [" J( U2 `+ C
Model specification, 模型的确定
" [; d* f" _) `* s* TModeling Statistics , 模型统计7 ?1 d' C% Z# o4 o6 x& E4 r/ l
Models for outliers, 离群值模型4 Y: M" j4 R' Y; T! d1 R, f
Modifying the model, 模型的修正& d6 I0 N, d; J) w( {2 |+ G
Modulus of continuity, 连续性模
/ z+ u K5 i) q; Q tMorbidity, 发病率
1 q' X6 U5 Y( E* A8 P! X% r! LMost favorable configuration, 最有利构形
7 o" }! O e9 T' c1 O8 {Multidimensional Scaling (ASCAL), 多维尺度/多维标度
" N0 N m7 Z( nMultinomial Logistic Regression , 多项逻辑斯蒂回归
$ ?& x. }- n9 P& I( I" u B8 o" H8 uMultiple comparison, 多重比较+ Q7 [, [* s% p
Multiple correlation , 复相关/ O) |& [. V% Y6 p( n2 o3 d. o8 g! Q
Multiple covariance, 多元协方差
* y: h, b2 Q& B$ rMultiple linear regression, 多元线性回归- x/ a0 ^0 t: h
Multiple response , 多重选项4 H: F6 f+ m. @" E! b/ j; \
Multiple solutions, 多解
& U' b# s( K$ [3 u; {/ H5 @Multiplication theorem, 乘法定理( n5 u/ ?: `! |4 i0 f8 N+ c! K
Multiresponse, 多元响应
5 M$ H$ K, g4 d4 l$ D: P6 sMulti-stage sampling, 多阶段抽样
' v, g+ x1 U. ^* q7 h4 W% P; P8 w" ?% QMultivariate T distribution, 多元T分布
; m8 N/ X7 g0 q% W* Q0 `% m6 v: RMutual exclusive, 互不相容; |- ] } G4 N2 m, S" F
Mutual independence, 互相独立
1 z: c0 @ | l# X9 I9 |Natural boundary, 自然边界
. w" H# z. K; T( T* d+ ^4 ONatural dead, 自然死亡
3 g# u6 K& M. v/ G; yNatural zero, 自然零6 q. {* l9 U6 x
Negative correlation, 负相关
) `/ ~- y! o* ^' ?4 x wNegative linear correlation, 负线性相关! K4 @# ]2 H3 ?0 [, ?
Negatively skewed, 负偏
7 b, ]4 u& N# zNewman-Keuls method, q检验
+ H0 R- o+ |( O, W- |+ DNK method, q检验1 O! |6 s3 p2 r- k
No statistical significance, 无统计意义
* V, H4 G' Z; A: @, i9 w+ i nNominal variable, 名义变量
3 A$ ~% |0 _& |& vNonconstancy of variability, 变异的非定常性
2 s$ V# L( k: n$ L0 B- ?Nonlinear regression, 非线性相关$ p& q; o; s! ~9 a9 w- ?$ L4 E
Nonparametric statistics, 非参数统计* {' X6 z3 _, q7 m) ^9 ]3 R5 X( b, K
Nonparametric test, 非参数检验6 [/ F1 p- g! c4 K, p% a( I y
Nonparametric tests, 非参数检验
7 O" v) c( f: _! U4 \Normal deviate, 正态离差
1 O% x1 L U! e3 R" O+ I& q) M+ CNormal distribution, 正态分布3 [% j6 C/ _# |& M4 y- b8 E
Normal equation, 正规方程组$ O! p4 ]8 l' u, ?% P# K
Normal ranges, 正常范围3 [% m" @1 M0 {! e
Normal value, 正常值9 O8 t$ n* l0 N. \
Nuisance parameter, 多余参数/讨厌参数0 L6 l/ u4 u( o( `! a4 R
Null hypothesis, 无效假设
. Y5 b8 [( Q+ |Numerical variable, 数值变量3 A; y8 c4 V- Q& o- u3 t! o+ t
Objective function, 目标函数- A( E' j4 z @! u3 a' w) D
Observation unit, 观察单位7 |" K9 Y, T/ c% Y& v+ { ^
Observed value, 观察值
3 d/ L; P4 W- o7 J7 U$ KOne sided test, 单侧检验0 J. b8 J$ {4 y: C2 E
One-way analysis of variance, 单因素方差分析
) V5 I% A2 U# b6 ] J$ r' s! COneway ANOVA , 单因素方差分析( J: k: p, o7 q/ O6 _9 w1 C$ x
Open sequential trial, 开放型序贯设计. [' U) A2 Y; b0 m
Optrim, 优切尾' g; F2 Y) \) I: ^2 J9 t
Optrim efficiency, 优切尾效率6 L" J8 g! Z# y( X& u- i
Order statistics, 顺序统计量4 y3 }; B; w) l% ~
Ordered categories, 有序分类
( t- g8 n+ q/ l+ o! |3 VOrdinal logistic regression , 序数逻辑斯蒂回归
3 |8 d" }+ ] Q& d+ ~3 ~" |Ordinal variable, 有序变量5 c( k( T. F! [& h+ n. w
Orthogonal basis, 正交基; Y0 u7 {* o/ Q) l5 M+ ?$ I
Orthogonal design, 正交试验设计0 S" z3 q+ G' d* P$ W0 r( t
Orthogonality conditions, 正交条件
9 j; a2 N, g0 g$ ?9 TORTHOPLAN, 正交设计 ) \1 B2 N4 I' c) T' h& T
Outlier cutoffs, 离群值截断点0 I! ?% _4 X: U) Y
Outliers, 极端值) [/ o0 A) Q# ?" ^: n
OVERALS , 多组变量的非线性正规相关
% F& e S( c! X) y) DOvershoot, 迭代过度6 U2 z' O" h6 s# y) \/ h$ f
Paired design, 配对设计# b5 `! |! c6 K$ w0 \
Paired sample, 配对样本( {4 v& A& d% {& t5 o
Pairwise slopes, 成对斜率
1 x, o' j+ |- sParabola, 抛物线/ x) e: n6 ~4 ~# O7 P8 z
Parallel tests, 平行试验
. { L9 L$ X- yParameter, 参数
2 z: p$ A) R8 F" f# A( sParametric statistics, 参数统计8 I" w8 }3 T5 s1 {+ h
Parametric test, 参数检验0 j! m7 q( Q! g# o, j! Z
Partial correlation, 偏相关* `2 z, h8 N! l0 L+ Z6 ^# m
Partial regression, 偏回归/ D/ h0 M& a" K# ` P1 o j& K2 t8 t. |
Partial sorting, 偏排序) A6 M% O e4 W1 E. O6 w$ Q- f
Partials residuals, 偏残差
/ M; _# L( y2 X9 \6 ~, hPattern, 模式5 @) z% x1 M5 A# ?; X* {# l; W
Pearson curves, 皮尔逊曲线' n& U* K3 z& q* B
Peeling, 退层4 R/ w% r1 `1 V7 W* D* Y( ~% H! |( h
Percent bar graph, 百分条形图
/ G/ R( t' S! u5 B: i5 sPercentage, 百分比
1 u( K6 c2 I5 S0 U" C+ G4 E' UPercentile, 百分位数
, I$ T$ k2 T% A/ F& G' `Percentile curves, 百分位曲线
) |+ b( o1 ?) `8 WPeriodicity, 周期性
) R0 k, _" d3 zPermutation, 排列8 z- |3 T5 v1 N, _8 j2 w8 n. Z4 h
P-estimator, P估计量
/ C7 ^/ a0 k, U M c+ b/ c2 N% wPie graph, 饼图
! J2 E% [$ D, k" j [# zPitman estimator, 皮特曼估计量
! M! ^* }4 B7 d* w. pPivot, 枢轴量
$ |4 }* ~ K$ D! mPlanar, 平坦- ^3 X( x9 }9 y7 V' C/ U
Planar assumption, 平面的假设$ L/ u$ W8 v, o H5 F' n `
PLANCARDS, 生成试验的计划卡+ q& j% G: C$ N) s" K% S
Point estimation, 点估计
% X. o9 q) e2 CPoisson distribution, 泊松分布4 C; M8 h @# D3 V- u5 `
Polishing, 平滑* z: u6 Z" m' _& F) x
Polled standard deviation, 合并标准差
* v" R7 i% J, Z, _* XPolled variance, 合并方差
( \+ f, y/ W! [5 ?8 b+ j4 t) N7 oPolygon, 多边图
* x$ S; U# v# \6 _, y9 @Polynomial, 多项式8 i' d% y) a& v. j+ ?( i2 [
Polynomial curve, 多项式曲线
( @/ ^7 F; w8 b6 |! B( q) sPopulation, 总体
+ a$ Z/ {! ~3 C& y8 }: k0 BPopulation attributable risk, 人群归因危险度
2 G$ i5 o" c5 Y, wPositive correlation, 正相关
' }1 ^- g6 w4 V6 UPositively skewed, 正偏1 L& x. J/ l+ U! J. n
Posterior distribution, 后验分布
. |) M8 H) _6 ~2 u8 V JPower of a test, 检验效能1 X+ y& l# {( x( Q" K
Precision, 精密度
& I/ ?) @' Z* Y! EPredicted value, 预测值
5 V- v/ U3 A% Y# [8 {" \Preliminary analysis, 预备性分析
8 K' I" A" \5 kPrincipal component analysis, 主成分分析* Z {1 ?& s+ Z7 H7 W( W; I: T
Prior distribution, 先验分布9 e- ^7 Q" @& [5 u" z
Prior probability, 先验概率9 p; Y8 P7 g# `: P
Probabilistic model, 概率模型# J3 m- @4 H6 |( v" r6 j
probability, 概率+ K0 s0 [& }: B
Probability density, 概率密度
% |1 J1 {+ p$ |1 v9 I: v. XProduct moment, 乘积矩/协方差
" A0 u$ m) ^, B( x9 i/ f* L0 S! HProfile trace, 截面迹图
+ g6 M! ^, T7 R/ l% N, B0 XProportion, 比/构成比( G0 p! |' L K7 {
Proportion allocation in stratified random sampling, 按比例分层随机抽样
, ~- Y' |& j0 |# j6 {3 h- t$ {; GProportionate, 成比例3 z) x1 U; z7 ^
Proportionate sub-class numbers, 成比例次级组含量3 M. a& L5 r8 U' |
Prospective study, 前瞻性调查 p: k( V- q4 k2 g2 F
Proximities, 亲近性 # `6 h. F c) f$ p- a% t3 U
Pseudo F test, 近似F检验2 [+ z0 @8 T% b6 H
Pseudo model, 近似模型7 Q. Q9 k E* x/ _! ^; k; B
Pseudosigma, 伪标准差
/ Z; U+ @# Y% r( W3 M% q( PPurposive sampling, 有目的抽样; v2 r# R$ X+ a& m$ k Y
QR decomposition, QR分解
/ G! a# ?8 K6 U8 |. A! M uQuadratic approximation, 二次近似
5 Y" c& V# M# tQualitative classification, 属性分类
$ P0 D5 _* e" j6 D! r; ^( X% W9 ^Qualitative method, 定性方法
: \* p ] `5 A. C+ SQuantile-quantile plot, 分位数-分位数图/Q-Q图
2 K! c1 x# F* B8 H7 NQuantitative analysis, 定量分析
: f0 U: m8 I: @! x5 q+ oQuartile, 四分位数: G" d% Z* E# ]" N* H( c
Quick Cluster, 快速聚类( s: S; n( k4 f4 x, {0 w: n' B
Radix sort, 基数排序
0 w0 R/ v: O0 C: \( Q9 \% H" wRandom allocation, 随机化分组7 X) f4 Z, O6 W4 V4 D D* m# O0 ]
Random blocks design, 随机区组设计
) |2 T1 ]5 b7 L: A0 v0 g. M! j' MRandom event, 随机事件
1 r; @4 S3 _9 Z1 X/ BRandomization, 随机化
) N, ~, |9 ^' {* R6 O5 K5 WRange, 极差/全距8 g8 c$ a6 k3 C- H* G
Rank correlation, 等级相关! K7 W9 Y1 i/ t' F" x
Rank sum test, 秩和检验
& c: P* M! f/ F1 @Rank test, 秩检验
1 K/ ^2 |% V( w8 iRanked data, 等级资料4 y. n# w& T1 x: O7 B7 U
Rate, 比率
" ^- P+ J0 V$ A5 \0 D$ K/ ], QRatio, 比例
; r. K, Y: c( \0 Y1 iRaw data, 原始资料; l2 D- b. S$ R. a7 [
Raw residual, 原始残差
* N! V! M/ R# x# k9 rRayleigh's test, 雷氏检验# Z' ]9 q( b& Y& u1 C
Rayleigh's Z, 雷氏Z值 0 `( e, g# `& S; D
Reciprocal, 倒数
( N$ Z, a q5 K- U) A; F! RReciprocal transformation, 倒数变换+ p, d( a9 w! ~: Y8 }/ d4 J
Recording, 记录
3 d9 w5 d- [# `Redescending estimators, 回降估计量
& u2 }/ }1 t y/ L E {& R3 ]! o! VReducing dimensions, 降维# Q/ \8 p- [/ u- q
Re-expression, 重新表达
( `! [" K/ j" oReference set, 标准组; h; W- d1 `& U+ J G
Region of acceptance, 接受域
- F1 c+ I4 M6 M0 p4 P+ Z6 o7 K- nRegression coefficient, 回归系数) q! ^& H; s: W; Z" {) j
Regression sum of square, 回归平方和% s! y5 x" n' d5 \
Rejection point, 拒绝点
% ?; d2 |) {+ YRelative dispersion, 相对离散度
4 a& T& P9 Y+ I0 YRelative number, 相对数
( q! z4 {+ R4 j# z; Y8 v& \& iReliability, 可靠性9 n8 d8 U8 [+ s7 `2 a0 I9 m% [
Reparametrization, 重新设置参数
- }% [) ~4 v9 l2 ]6 A3 jReplication, 重复
7 G7 \) ^* q3 Q R4 r, t6 p! ~* y5 M! S9 RReport Summaries, 报告摘要
+ s' n) ]3 |' W+ e. I3 nResidual sum of square, 剩余平方和
9 M; Z; Z9 |4 `) t2 R( z HResistance, 耐抗性9 u) T' J! N# P6 `1 z: m) I
Resistant line, 耐抗线
# @3 ]: n1 D" v! bResistant technique, 耐抗技术
/ E. A1 g# z, J; p7 qR-estimator of location, 位置R估计量; \" I+ c7 _! L
R-estimator of scale, 尺度R估计量7 Z& {/ |& G. @. s9 @. p, r/ ^
Retrospective study, 回顾性调查
# {; E' m" C: m6 uRidge trace, 岭迹. y- o( S4 d) |0 G" d
Ridit analysis, Ridit分析
' X; b! t* @8 p! S- r* s3 PRotation, 旋转4 }& S% ^8 }* e! E& B
Rounding, 舍入
& m2 c1 j: R. oRow, 行' i" B9 t+ y& r- V/ s
Row effects, 行效应( y5 \; n1 r# z. W
Row factor, 行因素
9 g( z* w7 A" F2 x6 ARXC table, RXC表
( `: x' F6 E2 X- y9 _- ?Sample, 样本
7 T, x6 Q) X5 `6 m" j0 A4 l+ F2 _Sample regression coefficient, 样本回归系数+ M. k& [+ m& R' c0 o4 t
Sample size, 样本量
' D+ n$ s! T9 t5 X1 E" dSample standard deviation, 样本标准差' h6 z5 L: H. n7 q6 h) B- g4 L Y
Sampling error, 抽样误差
' [1 w# S( t5 x4 q% E/ mSAS(Statistical analysis system ), SAS统计软件包
2 P6 D3 |. n" U& c& F- DScale, 尺度/量表
$ |8 N1 x& C" v; ]4 ~! _# KScatter diagram, 散点图* g( H" Z! s1 w% ~7 d7 ?8 r
Schematic plot, 示意图/简图- W. M' o, x& B, ^2 H/ Q
Score test, 计分检验
! a6 b1 O6 R6 X' | a) f3 PScreening, 筛检; |5 |3 v$ n! b) a6 R A2 X8 _
SEASON, 季节分析 & Z" p4 F4 c" c! }, i! ^
Second derivative, 二阶导数
1 ~7 h0 O. _7 M0 ASecond principal component, 第二主成分( B" m. | _ J* p& K
SEM (Structural equation modeling), 结构化方程模型 % @, M3 T, C% C9 y. K
Semi-logarithmic graph, 半对数图: x G# u6 z2 ], C- P, n# I9 e7 H
Semi-logarithmic paper, 半对数格纸8 }0 S+ y# R& j+ D4 V) S
Sensitivity curve, 敏感度曲线
4 C8 n. g8 H" R( g& M! U* B9 o( ZSequential analysis, 贯序分析& X; ~3 O' O# F4 B
Sequential data set, 顺序数据集
" B2 ^: w5 J% |% U1 R2 xSequential design, 贯序设计
% C1 N9 g' a4 J. A2 } kSequential method, 贯序法
; c' i. p+ `3 i7 X) {6 n C7 R4 vSequential test, 贯序检验法
/ h$ K: \1 o: wSerial tests, 系列试验) |8 a4 c) |2 h* R% q+ t6 a7 y ?
Short-cut method, 简捷法
( J7 S, K" g4 p, T K9 g% Z* `. ^7 e9 BSigmoid curve, S形曲线
$ F( d) _* U* C* t, gSign function, 正负号函数0 k7 t& l8 V, M$ x1 }
Sign test, 符号检验
% {. V. [; }# d: CSigned rank, 符号秩
m; E, b4 T* M( g3 nSignificance test, 显著性检验2 C5 K- m) L+ i% o3 r( |
Significant figure, 有效数字
: h1 u# C" {5 V- w0 t) s* E' D" @Simple cluster sampling, 简单整群抽样* T* o9 f9 V- E$ c( j0 I, Y
Simple correlation, 简单相关
( u' q& Z1 |2 M% E) cSimple random sampling, 简单随机抽样
& ]9 w) y% w8 d% \Simple regression, 简单回归
* B6 V0 l5 W5 w+ r1 b7 n6 tsimple table, 简单表/ h2 d1 P; w+ K
Sine estimator, 正弦估计量! b, Q* P$ }( b {* `
Single-valued estimate, 单值估计
1 g- z# y+ A* y# s# rSingular matrix, 奇异矩阵/ I' [5 k& Y" `
Skewed distribution, 偏斜分布
5 t0 J) u/ _! ^0 ~% N; W2 K8 U. jSkewness, 偏度
2 i8 D0 {% _5 j9 c mSlash distribution, 斜线分布 [: y2 t. }& ]: E7 Y' P9 @( V- I$ t* I
Slope, 斜率
1 o; Z! ?. X( V; CSmirnov test, 斯米尔诺夫检验
( k& k% e1 G6 O9 U+ H& w1 q& I6 g9 m9 JSource of variation, 变异来源
0 n( ?' W& J0 b" r) {Spearman rank correlation, 斯皮尔曼等级相关
3 p" B1 R' T! p1 w! q0 |Specific factor, 特殊因子" F: T. E) \* r( C) L' T; ?3 k
Specific factor variance, 特殊因子方差% m. N9 P5 O0 R+ Z+ q8 I, ?
Spectra , 频谱0 O" O6 E+ {- G$ U q) e
Spherical distribution, 球型正态分布5 f# M8 p8 @' f/ K* ?
Spread, 展布. h% B& {4 V) ~) K! b
SPSS(Statistical package for the social science), SPSS统计软件包
; ^% l& p( {4 q2 R; L! i. KSpurious correlation, 假性相关" e' b- H4 h6 O" x
Square root transformation, 平方根变换2 E- [$ v: A3 k. [2 K; F
Stabilizing variance, 稳定方差8 A, d$ A" Z1 v
Standard deviation, 标准差+ U) ^ e) b4 G/ N7 Z
Standard error, 标准误6 h+ s' B6 k# y \' `+ [3 t& b
Standard error of difference, 差别的标准误
1 E1 K& [+ i, l. m6 }! ]0 W" xStandard error of estimate, 标准估计误差
7 e- E+ a, C5 [# ^# ?( CStandard error of rate, 率的标准误0 p& @( b$ N; \
Standard normal distribution, 标准正态分布
+ F( n( c( L, N' UStandardization, 标准化2 `% t# ^( j+ I, V" I( k. b5 Q
Starting value, 起始值
, \4 g+ B- Y4 H7 g) bStatistic, 统计量
" E. z$ [3 i% H0 TStatistical control, 统计控制
F& F: I7 @& _0 Q+ O' E- uStatistical graph, 统计图
! X8 P5 z8 n; ]7 Q4 [Statistical inference, 统计推断
. Z" t3 v8 _& `Statistical table, 统计表$ z/ _- T7 m Z: R9 Q" }. w
Steepest descent, 最速下降法7 M7 {3 @& b, K( R3 F8 G3 c
Stem and leaf display, 茎叶图; c! G1 e' n' k6 {0 q% z
Step factor, 步长因子
0 `6 h* d: {( G2 w2 M0 W9 JStepwise regression, 逐步回归
. U/ |) ~) c. {/ lStorage, 存0 p6 Z9 ?! E8 C5 N, E( m4 W6 ~) X
Strata, 层（复数）
% g* f! u- u! z# }Stratified sampling, 分层抽样
/ s r* l* H$ lStratified sampling, 分层抽样4 y; `2 L! m- |0 |0 i1 K
Strength, 强度
- s _8 Y& _/ ?6 P& |5 j \Stringency, 严密性
! g6 i5 G# F8 o" _Structural relationship, 结构关系
/ U) g* l z, y7 L- V! c: [8 I4 RStudentized residual, 学生化残差/t化残差5 y; u. q- X( G w5 N
Sub-class numbers, 次级组含量
1 v' M" T* R" U7 l2 jSubdividing, 分割
5 G; g; C% X; r: t9 X. y+ g3 x% cSufficient statistic, 充分统计量
6 T1 ?$ g( R2 A9 `Sum of products, 积和
6 s! ^ o1 W a( U1 N9 }) k6 V8 j* @Sum of squares, 离差平方和
5 t! w+ o# @: V7 p+ p* e% GSum of squares about regression, 回归平方和
5 j+ L' L v# e3 ^Sum of squares between groups, 组间平方和! ^; x/ }) J6 |. @: Y5 v
Sum of squares of partial regression, 偏回归平方和' w" |' P5 y7 `" p1 u5 Q
Sure event, 必然事件
n: L$ _* b$ X' dSurvey, 调查
! v7 }2 [/ Y. j3 HSurvival, 生存分析3 K3 b2 R [( q; b- s
Survival rate, 生存率
, e% s- M4 i! a9 G+ R& N/ \3 {Suspended root gram, 悬吊根图: l8 G a2 h, g; I1 O+ l
Symmetry, 对称
! o" J5 I: \: LSystematic error, 系统误差
) W/ ]2 k* N! uSystematic sampling, 系统抽样9 s; B) t/ w8 g- T. S- T
Tags, 标签5 v/ z3 _) Z5 T
Tail area, 尾部面积
. z9 J6 s/ M* F+ B$ i nTail length, 尾长
& M0 g9 E% N' k9 z" MTail weight, 尾重
9 G; [ m- e, o8 xTangent line, 切线7 B0 F7 y/ a5 f9 R, J
Target distribution, 目标分布( H. f: Q9 N" I6 r
Taylor series, 泰勒级数0 |* g+ _1 ?: o+ ?
Tendency of dispersion, 离散趋势3 C7 m; o8 c! _+ M4 ]* v
Testing of hypotheses, 假设检验
. S8 R, @( M! Z$ V) @& gTheoretical frequency, 理论频数
5 [5 p# r0 k% E, UTime series, 时间序列+ o% ^) `( T% z( f0 a# j
Tolerance interval, 容忍区间
# r) x! L& w& l& X8 M5 C+ u) LTolerance lower limit, 容忍下限
0 A$ H* v6 g6 i5 ~, A; H9 {' M6 y. RTolerance upper limit, 容忍上限; H7 `0 ? q+ H) S0 f5 K! T# x
Torsion, 扰率
5 m8 c( W0 e* J5 d( kTotal sum of square, 总平方和9 G3 l5 q, d# @- Z
Total variation, 总变异
: m" C* |. Q$ G' M& F/ t) q, kTransformation, 转换$ e) u5 X7 `0 A9 O: _
Treatment, 处理1 G7 {; C7 Y- t9 g7 m& j7 r% |( ?6 J
Trend, 趋势
7 N9 `! ^: f, R! v* ^ jTrend of percentage, 百分比趋势2 r8 i# G: S3 |3 ]- B2 I$ F& m' s
Trial, 试验, L }. S2 O6 F( J! _% p+ L
Trial and error method, 试错法
' u$ y1 w4 K# x7 M1 \* a& NTuning constant, 细调常数
' H5 y5 c" X- {4 XTwo sided test, 双向检验
% g u: A; a R% ^4 V$ TTwo-stage least squares, 二阶最小平方! B H+ c. Y ~: o. N
Two-stage sampling, 二阶段抽样
2 R' q- X! y; l1 K: JTwo-tailed test, 双侧检验$ Q5 b0 w2 m$ `/ b# z# o4 T5 g( D8 m
Two-way analysis of variance, 双因素方差分析, l$ b7 g% T7 I |
Two-way table, 双向表
1 U7 s! v X; P0 h8 I+ tType I error, 一类错误/α错误
1 v3 }6 A' q, HType II error, 二类错误/β错误" @ l3 s! H+ @& K# h, j
UMVU, 方差一致最小无偏估计简称% ?1 [% w0 n) X" m$ ]3 b
Unbiased estimate, 无偏估计
5 m' `$ b X. r4 b( }7 ?# aUnconstrained nonlinear regression , 无约束非线性回归
5 ]' v! \( r, f+ xUnequal subclass number, 不等次级组含量
5 E* U9 z6 [$ i4 n9 K; vUngrouped data, 不分组资料* s# v6 G9 G6 A$ `- h6 J- C
Uniform coordinate, 均匀坐标( F! Z' Q c9 \8 n3 k
Uniform distribution, 均匀分布" n4 f8 M% q' R$ W
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计: I( G/ l) f4 Z7 x- Y3 Z
Unit, 单元: z" @/ q) G Z9 `" G
Unordered categories, 无序分类
* ?3 `! _8 |3 Q5 ^, Y" gUpper limit, 上限
4 f/ [% {. _ PUpward rank, 升秩1 H6 D( h6 ^' S U F. H$ _
Vague concept, 模糊概念" @5 l' y0 b. G' O$ m3 a! w5 q
Validity, 有效性: p. D, Q2 B4 e' B0 _7 T
VARCOMP (Variance component estimation), 方差元素估计
1 |) M8 U& |8 p" N, l! d Z5 ~Variability, 变异性! {% z( h% b3 _+ @
Variable, 变量
$ \; A. R1 w/ Q: d0 D+ KVariance, 方差
3 B3 p: `) R* G5 ~8 DVariation, 变异 \* F( K3 ]6 ]
Varimax orthogonal rotation, 方差最大正交旋转" ?$ B0 [' i, D! }' K+ m. L
Volume of distribution, 容积 Y9 D3 n! X4 o8 [
W test, W检验9 U2 j% \. R+ a9 i; O
Weibull distribution, 威布尔分布8 {( E# X( ?) _7 d% ?
Weight, 权数
+ [- d. }% J# S7 b" pWeighted Chi-square test, 加权卡方检验/Cochran检验* A$ |9 ^; w0 ~: r, t9 Q3 w
Weighted linear regression method, 加权直线回归
8 ^0 y7 m3 {$ k' O* \; F& TWeighted mean, 加权平均数, F' P( u( F. n0 Y; F: W4 c3 R% B
Weighted mean square, 加权平均方差* D7 ^% Z: E6 G6 u
Weighted sum of square, 加权平方和
. Q, X$ [+ D$ D' t3 FWeighting coefficient, 权重系数; N/ {5 E+ N2 |- E: @" f8 F
Weighting method, 加权法
7 j3 n3 {1 ] X$ CW-estimation, W估计量
& e9 ?$ d8 B* ~6 BW-estimation of location, 位置W估计量1 K0 o ?1 M2 O- w( e9 }
Width, 宽度
+ E: C- ?! t& j" oWilcoxon paired test, 威斯康星配对法/配对符号秩和检验; y4 X X Y$ o2 `9 w- {# n1 T7 v
Wild point, 野点/狂点% z0 ~1 m. Q5 y( G z( v5 k/ u
Wild value, 野值/狂值
# E9 o# W" x# U: zWinsorized mean, 缩尾均值
$ z$ B& l4 p- U; m* LWithdraw, 失访
0 L( @$ C6 D$ c# K) g6 V0 ZYouden's index, 尤登指数3 Z5 j: x% |. d3 R5 }( y% s; p" n" Z
Z test, Z检验
$ i; q+ S$ S& j# ?0 pZero correlation, 零相关5 d# D$ w- |9 d% C c
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
